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摘要:
随着城市工程建设的发展，建筑工程事故问题愈发突出，采用传统方法求取的岩土参数区间无法满足实际工程需要。基于无监督学习思想，选取工程性质较差的泥炭质土，结合工程经验选用8个物理指标作为输入集，利用主成分分析（priciple components analysis, PCA）算法实现多样本多参数去耦合的降维处理，得出各物理指标相关性及敏感度，结合其相关性及敏感度赋予不同埋深泥炭质土物理指标的综合评价值。利用k-means聚类分析泥炭质土物理指标、综合评价值及工程特性之间的关系，为岩土参数选取提供理论基础。采用监督学习方法——BP神经网络算法分析无监督结果，验证（PCA—k-means）算法模型的合理性。将通过聚类分析得到的正态样本利用多种截尾法优化，得到可靠取值区间，并将取值结果与实际工程取值比较，验证了该模型工程参数取值的合理性。该算法模型具有较好的工程应用价值，所得研究结果可为工程勘察、设计、施工参数取值提供参考，也能为岩土参数取值分析提供新的分析方法。
Abstract:With the development of urban engineering construction, the issue of construction engineering accidents has become more and more prominent. The geotechnical parameter interval obtained by using the traditional methods cannot meet the needs of actual engineering. Based on the idea of unsupervised learning, the peaty soil with the worst engineering properties is considered, and 8 physical indexes are selected as the input set. The principal component analysis (PCA) algorithm is used to realize the dimensionality reduction of multi-sample and multi-parameter decoupling, and the correlation and sensitivity of each physical index is obtained. Combined with its correlation and sensitivity, the comprehensive evaluation value of physical indexes of peat soil with different buried depths is given. The k-means clustering is used to analyze the relationship among physical index, and comprehensive evaluation value and engineering characteristics of peaty soil provide a theoretical basis for the selection of geotechnical parameters. The supervised learning method-BP neural network algorithm is used to analyze the unsupervised results and verify the accuracy of the (PCA—k-means) algorithm model. The normal samples obtained by clustering analysis are optimized by a variety of truncation methods to obtain a reliable value range, and the value results are compared with the actual engineering values to verify the rationality of the model engineering parameters. The algorithm model is of good engineering application value. The research results can provide references for engineering investigation, design and construction parameter values, and also provide a new analysis method for geotechnical parameter value analyses.
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表 1 各层泥炭质土的物理指标统计表
Table 1. Statistical table of physical indexes of peaty soil in each layer
地层编号 ρ
/（g·cm−3）Gs ω
/%ωL
/%ωP
/%e a1-2
/MPa−1wu
/%$\text{③}_1^1$ 1.61 2.30 110.1 135.4 100.0 2.49 1.62 24.33 $\text{③}_2 $ 1.42 2.42 101.2 119.2 87.2 2.40 1.32 18.36 $\text{④}_1 $ 1.25 1.95 145.7 182.1 146.4 2.93 1.49 40.10 $\text{⑤}_{12}$ 1.27 1.97 130.6 174.3 140.6 2.52 1.12 38.77 
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表 2 不同物理指标间的相关性系数
Table 2. Correlation between different physical indicators
物理指标 ρ GS ω ωL e a1-2 ωP wu ρ 1.00 GS 0.64 1.00 w 0.87 0.55 1.00 wL 0.89 0.59 0.94 1.00 e 0.85 0.85 0.94 0.87 1.00 a1-2 0.62 0.42 0.81 0.68 0.85 1.00 wP 0.85 0.58 0.82 0.93 0.58 0.49 1.00 wu 0.83 0.66 0.73 0.78 0.70 0.45 0.80 1.00
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表 3 各物理指标敏感度统计表
Table 3. Sensitivity statistics of each physical index
物理指标编码 X1（ρ） X2 （GS） X3 （ω） X4（ωL） X5（e） X6（a1-2） X7 （ωP） X8 （wu） 敏感度符号 r1 r2 r3 r4 r5 r6 r7 r8 敏感度值 0.2349 0.2069 0.2540 0.2428 0.2608 0.2151 0.2410 0.2281
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表 4 各组泥炭质土综合评价值排序
Table 4. Ranking of comprehensive evaluation of the peaty soil
组类 综合评价值 物理指标平均值 ρ/（g·cm−3） ω/% Gs e ωL/% ωP/% a1-2/MPa-1 wu/% 1 –1.295 1.565 57.590 2.517 1.536 68.690 42.690 0.722 8.100 2 –1.162 1.533 67.980 2.397 1.565 71.730 44.910 0.812 12.670 3 –1.096 1.499 68.280 2.428 1.699 76.180 48.270 1.103 11.690 4 –1.035 1.483 72.120 2.436 1.824 84.800 49.560 0.977 12.270 5 –0.928 1.452 73.690 2.238 1.882 92.400 58.890 0.850 13.678 6 –0.946 1.454 78.070 2.426 1.971 90.320 53.550 1.121 12.100 7 –0.900 1.455 82.180 2.426 1.957 95.363 62.181 0.833 13.318 … … … … … … … … … … 34 1.293 1.115 211.200 1.796 4.406 228.270 149.400 3.802 43.750 35 1.496 1.134 220.200 1.164 4.761 228.710 144.100 4.718 44.346 36 1.566 1.117 232.700 1.311 4.818 238.770 149.310 5.031 40.817 37 1.861 1.121 247.000 0.996 5.327 249.400 156.300 6.006 41.710 38 2.574 1.079 287.182 0.990 5.839 304.936 207.800 5.978 56.455
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表 5 不同截尾法的原物理指标区间范围
Table 5. Original physical index range of different censoring methods
物理指标 均值 标准差 偏度系数 变异系数 3σ区间范围 c33区间范围 c3区间范围 e 3.03 1.20 0.94 0.39 [0,6.63] [0.56,7.76] [0，7.76] ω/% 133.02 62.09 0.93 0.46 [0,319.29] [4.48,377.03] [0,377.03] ωL/% 148.63 61.26 0.87 0.41 [0,332.41] [18.14,385.71] [0,385.71]
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表 7 不同截尾法的新样本区间范围
Table 7. Range of new sample intervals for different censoring methods
物理指标 均值 标准差 偏度系数 变异系数 3σ区间范围 c33区间范围 c3区间范围 e 2.19 0.40 0.39 0.18 [0.99,3.39] [1.45,3.55] [0.99,3.55] ω/% 88.68 17.40 0.39 0.18 [36.48,140.88] [43.26,147.66] [36.48,140.88] ωL/% 105.55 22.11 0.28 0.20 [39.22,171.88] [45.41,178.07] [39.22,178.08] ρ/（g·cm−3） 1.40 0.08 0.08 0.06 [1.13,1.66] [1.15,1.67] [1.13,1.67] Gs 2.25 0.45 –3.08 0.20 [0.89,3.61] [1.15,3.55] [1.15,3.61] a1-2/MPa−1 1.24 0.56 1.56 0.45 [0,2.93] [0.43,3.81] [0,2.93] ωP/% 68.76 18.06 0.38 0.26 [14.57,122.97] [21.48,129.88] [14.57,129.88] wu/% 17.63 7.64 2.02 0.43 [0,40.57] [10.17,56.06] [0,56.06]
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表 8 各层泥炭质土设计参数检验结果
Table 8. Test results of design parameters of the peaty soil in each layer
地层
编号ρ
/（g·cm−3）ω
/%e IL a1-2
/MPa−1综合
评价所属类 $ \text{③}_1^1$ 1.37 103.0 2.41 0.15 1.63 −0.23 第一类 $\text{③}_2 $ 1.39 91.1 2.33 0.12 1.30 −0.26 第一类 $\text{④}_1 $ 1.20 142.3 2.92 −0.14 1.47 −0.08 第一类 $\text{⑤}_{12} $ 1.26 127.7 2.53 −0.28 1.12 −0.16 第一类
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